.Rhistory

library(NGS.Tools.BICseq)
?run.bicseq.cnv.pipeline
set.seed(12345);
data.directories <- paste(.libPaths(), '/BoutrosLab.pipeline.bicseq', sep = '');
data.directories
data.directories <- c('./', data.directories);
data.directorie
data.directories
data.directories <- c(getwd(), data.directories);
data.directories
library(NGS.Tools.BICseq)
?run.bicseq.cnv.pipeline
set.seed(12345);
# create a list of potential locations for the datasets
data.directories <- paste(.libPaths(), '/NGS.Tools.BICseq', sep = '');
data.directories <- c('./', data.directories);
# look in the Rcheck directory to get dataset file
data.directories <- c(getwd(), data.directories);
# search all the locations for the normal file
file.checks <- file.exists(paste(data.directories, 'extdata/normal_sorted.bam', sep = '/'));
# check to see if the file was actually found
if (any(file.checks)) {
data.directory <- data.directories[order(file.checks, decreasing = TRUE)[1]];
} else {
stop('Unable to find dataset file for processing');
}
normal <- paste(data.directory, 'extdata/normal_sorted.bam', sep = '/');
normal
tumour
# search all the locations for the normal file
file.checks <- file.exists(paste(data.directories, 'extdata/tumor_sorted.bam', sep = '/'));
# check to see if the file was actually found
if (any(file.checks)) {
data.directory <- data.directories[order(file.checks, decreasing = TRUE)[1]];
} else {
stop('Unable to find dataset file for processing');
}
tumour <- paste(data.directory, 'extdata/tumor_sorted.bam', sep = '/');
tumour
run.bicseq.cnv.pipeline(
normal = normal,
tumour = tumour,
chr = c('chr22')
);
library(BICseq)
set.seed(12345);
# create a list of potential locations for the datasets
data.directories <- paste(.libPaths(), '/NGS.Tools.BICseq', sep = '');
data.directories <- c('./', data.directories);
# look in the Rcheck directory to get dataset file
data.directories <- c(getwd(), data.directories);
# search all the locations for the normal file
file.checks <- file.exists(paste(data.directories, 'extdata/normal_sorted.bam', sep = '/'));
# check to see if the file was actually found
if (any(file.checks)) {
data.directory <- data.directories[order(file.checks, decreasing = TRUE)[1]];
} else {
stop('Unable to find dataset file for processing');
}
normal <- paste(data.directory, 'extdata/normal_sorted.bam', sep = '/');
# search all the locations for the normal file
file.checks <- file.exists(paste(data.directories, 'extdata/tumor_sorted.bam', sep = '/'));
# check to see if the file was actually found
if (any(file.checks)) {
data.directory <- data.directories[order(file.checks, decreasing = TRUE)[1]];
} else {
stop('Unable to find dataset file for processing');
}
tumour <- paste(data.directory, 'extdata/tumor_sorted.bam', sep = '/');
data <- run.bicseq.cnv.pipeline(
normal = normal,
tumour = tumour,
chr = c('chr22')
);
q()
library(NGS.Tools.BICseq)
set.seed(12345);
# create a list of potential locations for the datasets
data.directories <- paste(.libPaths(), '/NGS.Tools.BICseq', sep = '');
data.directories <- c('./', data.directories);
# look in the Rcheck directory to get dataset file
data.directories <- c(getwd(), data.directories);
# search all the locations for the normal file
file.checks <- file.exists(paste(data.directories, 'extdata/normal_sorted.bam', sep = '/'));
# check to see if the file was actually found
if (any(file.checks)) {
data.directory <- data.directories[order(file.checks, decreasing = TRUE)[1]];
} else {
stop('Unable to find dataset file for processing');
}
normal <- paste(data.directory, 'extdata/normal_sorted.bam', sep = '/');
# search all the locations for the normal file
file.checks <- file.exists(paste(data.directories, 'extdata/tumor_sorted.bam', sep = '/'));
# check to see if the file was actually found
if (any(file.checks)) {
data.directory <- data.directories[order(file.checks, decreasing = TRUE)[1]];
} else {
stop('Unable to find dataset file for processing');
}
tumour <- paste(data.directory, 'extdata/tumor_sorted.bam', sep = '/');
data <- run.bicseq.cnv.pipeline(
normal = normal,
tumour = tumour,
chr = c('chr22')
);
str(data)
data$bins
head(data$bins)
str(data)
data$seg.summary
head(data$summary.seg))
str(data)
plot(data[[seg.summary]]$start, data[[seg.summary]]$ratio)
?plot
plot(x = data$seg.summary$start, y = data$seg.summary$ratio)
library(plotting.general)
?create.scatterplot
create.scatterplot(data = data$seg.summary, x = 'start', y = 'ratio')
create.scatterplot(data = data$seg.summary, x = 'start', y = 'ratio', ylab = 'Ratio', xlab = 'Start Position')
create.scatterplot(data = data$seg.summary, x = 'start', y = 'ratio', ylab = 'Ratio', xlab = 'Start Position') + geom_point(aes(size = log10.pvalue))
getwd()
tumour <- '/mnt/hpf/largeprojects//adam/ewings_genomes/LP6005727-DNA_B01/Assembly/LP6005727-DNA_B01.bam'
normal <- '/mnt/hpf/largeprojects/adam/ewings_genomes/LP6005726-DNA_B01/Assembly/LP6005726-DNA_B01.bam'
run.bicseq.cnv.pipeline(normal = normal, tumour = tumour, chr = 'chr22')
data <- run.bicseq.cnv.pipeline(normal = normal, tumour = tumour, chr = 'chr22')
head(data$seg.summary)
create.scatterplot(data = data$seg.summary, x = 'start', y = 'ratio', ylab = 'Ratio', xlab = 'Start Position') + geom_point(aes(size = log10.pvalue))
plot.object <- create.scatterplot(data = data$seg.summary, x = 'start', y = 'ratio', ylab = 'Ratio', xlab = 'Start Position') + geom_point(aes(size = log10.pvalue))
write.plot(filename = '~/Desktop/chr22_LP6005727_B01_cnv.pdf', plot = plot.object, resolution = 900, width = 10, height = 8)
library(DNACopy)
source("http://bioconductor.org/biocLite.R")
?BiocUpgrade
source("http://bioconductor.org/biocLite.R")
biocLite("BiocUpgrade")
source("http://bioconductor.org/biocLite.R")
biocLite("DNAcopy")
library(DNACopy)
library(DNAcopy)
ls()
head(data$seg.summary)
data$seg.summary$read_ratio <- data$seg.summary$sampleReads / data$seg.summary$referenceReads
head(data$seg.summary)
data$seg.summary$log2_read_ratio <- log2(data$seg.summary$sampleReads / data$seg.summary$referenceReads)
head(data$seg.summary)
create.scatterplot(data = data$seg.summary, x = 'start', y = 'log2_read_ratio', xlab = 'Start Position', ylab = 'log2_read_ratio') + geom_point(aes(size = log10.pvalue))
plot.object <- create.scatterplot(data = data$seg.summary, x = 'start', y = 'log2_read_ratio', xlab = 'Start Position', ylab = 'Read Ratio [log2]') + geom_point(aes(size = log10.pvalue))
?CNA
head(data)
head(data$seg.summary)
?CNA
data(coriell)
head(coriell)
?coriell
CNA.object <- CNA(cbind(coriell$Coriell.05296), coriell$Chromosome, coriell.Position, data.type = 'logratio', sampleid = 'c05296')
CNA.object <- CNA(cbind(coriell$Coriell.05296), coriell$Chromosome, coriell$Position, data.type = 'logratio', sampleid = 'c05296')
CNA.object
smoothed.CNA.object <- smooth.CNA(CNA.object)
smoothed.CNA.object
segment.smoothed.CNA.object <- segment(smoothed.CNA.object, verbose = 1)
segment.smoothed.CNA.object
plot(segment.smoothed.CNA.object, plot.type = 'w')
plot(CNA.object, plot.type = 'w')
str(CNA.object)
plot(CNA.object$c05296, plot.type = 'w')
segment.CNA.object <- segment(CNA.object, verbose = 1)
plot(segment.CNA.object, plot.type = 'w')
plot(segment.smoothed.CNA.object, plot.type = 'w')
head(data)
CNA.object <- CNA(cbind(data$seg.summary$log2_read_ratio), data$chrom, data$start, data.type = 'logratio', sampleid = 'B01')
CNA.object <- CNA(cbind(data$seg.summary$log2_read_ratio), data$chrom, as.numeric(data$start), data.type = 'logratio', sampleid = 'B01')
head(data$chrom)
head(data$Chrom)
names(data)
CNA.object <- CNA(cbind(data$seg.summary$log2_read_ratio), data$seg.summary$chrom, as.numeric(data$seg.summary$start), data.type = 'logratio', sampleid = 'B01')
head(CNA.object)
plot(CNA.object, plot.type = 'w')
segment.CNA.object <- segment(smoothed.CNA.object, verbose = 1)
plot(segment.CNA.object, plot.type = 'w')
segment.CNA.object <- segment(CNA.object, verbose = 1)
plot(segment.CNA.object, plot.type = 'w')
summary(data$seg.summary$log2_read_ratio)
summary(data$seg.summary$ratio)
CNA.object <- CNA(cbind(data$seg.summary$ratio), data$seg.summary$chrom, as.numeric(data$seg.summary$start), data.type = 'logratio', sampleid = 'B01')
segment.CNA.object <- segment(CNA.object, verbose = 1)
plot(segment.CNA.object, plot.type = 'w')
CNA.object <- CNA(cbind(data$seg.summary$log2_read_ratio), data$seg.summary$chrom, as.numeric(data$seg.summary$start), data.type = 'logratio', sampleid = 'B01')
segment.CNA.object <- segment(CNA.object, verbose = 1)
plot(segment.CNA.object, plot.type = 'w')
CNA.object <- CNA(cbind(data$seg.summary$read_ratio), data$seg.summary$chrom, as.numeric(data$seg.summary$start), data.type = 'logratio', sampleid = 'B01')
segment.CNA.object <- segment(CNA.object, verbose = 1)
plot(segment.CNA.object, plot.type = 'w')
smoothed.CNA.object <- smooth.CNA(CNA.object)
segment.smoothed.CNA.object <- segment(smoothed.CNA.object, verbose = 1)
plot(segment.CNA.object, plot.type = 'w')
segment.CNA.object
head(data$seg.summary)
dim(data$bin)
head(data$bin)
data$bin$log2ratio <- log2(data$bin$ratio)
head(data$bin$log2ratio)
log2(-0.6780)
CNA.object <- CNA(cbin(data$bin$ratio), data$bin$chrom, as.numeric(data$bin$start), data.type = 'ratio', sampleid = 'B01')
segment.CNA.object <- segment(CNA.object, verbose = 1)
plot(segment.CNA.object, plot.type = 'w')
CNA.object <- CNA(cbind(data$bin$ratio), data$bin$chrom, as.numeric(data$bin$start), data.type = 'ratio', sampleid = 'B01')
source('~/.active-rstudio-document', echo=TRUE)
smoothed.CNA.object <- smooth.CNA(CNA.object)
segment.smoothed.CNA.object <- segment(smoothed.CNA.object, verbose = 1)
plot(segment.smoothed.CNA.object, plot.type = 'w')
plot(segment.CNA.object, plot.type = 'w')
head(coriell)
?coriell
head(coriell)
sessionInfo()
dir()
library(NGS.Tools.BICseq)
Rprof
?Rprof
library(NGS.Tools.BICseq)
dir()
dir('./inst/extdata')
require(NGS.Tools.BICseq)
tumour <- 'inst/extdata/tumor_sorted.bam'
normal <- 'inst/extdata/normal_sorted.bam'
data <- NGS.Tools.BICseq::run.bicseq.cnv.pipeline(
tumour=tumour,
normal=normal
)
data <- NGS.Tools.BICseq::run.bicseq.cnv.pipeline(
tumour=tumour,
normal=normal,
chr='chr22'
)
head(data)
str(data)
plot(data$seg.summary)
plot(data$seg.summary$log10.pvalue)
segs <- getBICseq(object=data$object, bin=100, lambda=2, win=200, quant=0.95, mult=1)
library(BICseq)
segs <- getBICseq(object=data$object, bin=100, lambda=2, win=200, quant=0.95, mult=1)
segs <- getBICseg(object=data$object, bin=100, lambda=2, win=200, quant=0.95, mult=1)
head(segs)
str(segs)
plot(segs)
plot(segs, sampleName='Demo', save=FALSE, plotBin=TRUE, chromOrder=c(1:22, 'X', 'Y'))
plot(segs, sampleName='Demo', save=FALSE, plotBin=TRUE, chromOrder=c(22))
plot(segs, sampleName='Demo', save=FALSE, plotBin=TRUE, chromOrder=c('22'))
plot(segs, sampleName='Demo', save=FALSE, plotBin=TRUE, chromOrder=c('chr22'))
?getBICseg
sessionInfo()
getwd()
library(devtools)
load_all(pkg='.')
run.bicseq.cnv.pipeline
head(data)
tumour
normal
data <- run.bicseq.cnv.pipeline(tumour=tumour, normal=normal)
data <- run.bicseq.cnv.pipeline(tumour=tumour, normal=normal, chr='chr22')
str(data)
plot(data$segs)
plot(data$segs, plotBin = TRUE)
plot(data$segs, sampleName='Demo', plotBin=TRUE)
plot(data$segs, sampleName='Demo', plotBin=TRUE, save=FALSE)
BICseq::plot(data$segs, sampleName='Demo', plotBin=TRUE, save=FALSE)
getwd()
old.dir <- getwd()
setwd('/mnt/hpf//largeprojects/adam/projects//ewings_genomes/data/LP6005726-DNA_A01__LP6005727-DNA_A01/raw//wgs//illumina/')
dir()
tumour <- 'LP6005727-DNA_A01.bam'
normal <- 'LP6005726-DNA_A01.bam'
data <- run.bicseq.cnv.pipeline(tumour = tumour, normal = normal)
getwd()
ls()
head(segs)
str(segs)
segs
data$seg.summary
unique(data$seg.summary$chrom)
ls()
create.histogram
library(plotting.general)
create.histogram
default.histogram.theme(base_size = 24)
default.histogram.theme
names(sv_data)
q()
library(devtools)
load_all(pkg='.')
sessionInfo()
bicseq <- BICseq(sample=tumour.bam, reference=normal.bam, seqNames=c(1:22, 'X', 'Y'))
tumour.bam <- '/usr/local/src/bicseq/BICseq/test_data/tumor_sorted.bam'
normal.bam <- '/usr/local/src/bicseq/BICseq/test_data/normal_sorted.bam'
bicseq <- BICseq(sample=tumour.bam, reference=normal.bam, seqNames=c(1:22, 'X', 'Y'))
bicseq <- BICseq(sample=tumour.bam, reference=normal.bam, seqNames=c('chr22'))
segs <- getBICseg(object = bicseq, bin = 100, lambda = 2, winSize = 200, quant = 0.95, mult = 1)
segs <- BICseq::getBICseg(object = bicseq, bin = 100, lambda = 2, winSize = 200, quant = 0.95, mult = 1)
source('/usr/local/src/bicseq/BICseq/R Package/BICseq/R/SupportingFunctions.R')
segs <- BICseq::getBICseg(object = bicseq, bin = 100, lambda = 2, winSize = 200, quant = 0.95, mult = 1)
segs <- getBICseg(object = bicseq, bin = 100, lambda = 2, winSize = 200, quant = 0.95, mult = 1)